Move over keyword density, semantics are the next big thing in search engine optimisation. Semantic searches are searches where search engines try to tease out the relationship between search terms and find related content. Semantic searches rely as much on latent search indexing or the density of related, secondary terms as they do the main key search terms the user inputs. Let's look at the importance of semantics and how it impacts SEO.

The Importance of Semantics

Latent semantic indexing, or the search engine categorisation of your content based on the words and phrases used in the content, impacts the types of searches your content comes up in. Simply repeating a keyword phrase over and over again now not only results in the quality score of the content being low and the content penalised as spammy, but neglecting the addition of related terms and context queues search engines use to categorise content will result in it coming up in the wrong types of searches.

For example, when talking about sets, make it clear if the content is about sets of games, tea sets, data sets or some other type of set. Discuss different types of data sets or spell out several types of game sets so that the search engine understands the overall topic of your text.

How Semantics Affect SEO

The semantics, or related terms to the topic, used in the content are the primary factor for search engines when determining if it fits the intended question behind the user’s search query. Semantic queries are used to find content that isn’t an exact match because nothing is an exact match for your search term or presents the most closely related content to the niche you’re seemingly searching for.

When planning the SEO of new content, plan on using latent semantic indexing or LSI terms at half the rate of the key search term so that your effort to rank well for context based searches doesn’t hurt the search results ranking for the main search term.

A side benefit of using secondary search terms in context with the key search term is that it improves the odds that searches for the secondary search term will still bring up your site, while searches for both sets of terms will yield your content in the results. After all, semantic searches will bring up closely related content based on these secondary terms and their context even if the user’s search term or query doesn’t include anything specifically spelled on the webpage.

What you should not do when writing content is address so many topics that Google cannot determine its context, include so many related keywords at a high density that it risks being hit with a spam penalty or having so many keywords repeated through the text that search engines don’t know what the main keywords are. You can reduce this issue by creating unique pieces of content for each topic or search term so that the SEO of each can be tailored to rank well.

Also apply semantic markups to your webpages, though this is supplementary to the SEO of the content itself.

Does Voice Search Eliminate the Need to Worry about Semantics?

Semantics is less of an issue if the search is a conversational search, but you can even use semantics to your advantage by listing the full question in the title or section headers of the content before answering it. For example, an article on “What is a router?” should have text including terms like computer or workbench so that Google knows if you’re talking about internet routers or the hand tool.

However, you should avoid rewording the query to include secondary, latent search terms and using that text as the first sentence in the answer to the query, since this annoys readers and can result in key search term repetition that penalises your otherwise perfect voice search optimisation.

Conversely, latent semantic indexing that suggests what question you’re trying to answer with the content can help you rank well with conversational search queries even if that exact question isn’t listed on the webpage.

Conclusion

In short, semantics are the words and phrases that help search engines determine the context of the content and determine how well it fits the intended query of the user. Related semantic search terms should be included in the content to help search engines identify the context of the content and improve the odds it comes up in related queries. Conversational searches don’t negate the need to write content with latent semantic indexing.